from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 13.0 | 32.100641 |
| daal4py_KNeighborsClassifier | 0.0 | 5.0 | 20.274588 |
| KNeighborsClassifier_kd_tree | 0.0 | 5.0 | 46.531391 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 44.499347 |
| KMeans_tall | 0.0 | 1.0 | 42.518739 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 19.551095 |
| KMeans_short | 0.0 | 0.0 | 23.062622 |
| daal4py_KMeans_short | 0.0 | 0.0 | 13.428654 |
| LogisticRegression | 0.0 | 1.0 | 22.295667 |
| daal4py_LogisticRegression | 0.0 | 1.0 | 12.816701 |
| Ridge | 0.0 | 0.0 | 25.263209 |
| daal4py_Ridge | 0.0 | 0.0 | 8.460757 |
| total | 0.0 | 33.0 | 10.885282 |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | throughput | latency | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.132 | 0.005 | 1000000 | 1000000 | 100 | brute | -1 | 1 | 6.079 | NaN | 0.978 | 0.984 | 0.486 | 0.006 | 0.271 | 0.012 | See |
| 1 | KNeighborsClassifier | predict | 29.570 | 0.301 | 1000000 | 1000 | 100 | brute | -1 | 1 | 0.000 | 0.030 | 0.978 | 0.984 | 3.712 | 0.015 | 7.966 | 0.087 | See |
| 2 | KNeighborsClassifier | predict | 0.195 | 0.018 | 1000000 | 1 | 100 | brute | -1 | 1 | 0.004 | 0.000 | 0.978 | 0.984 | 0.101 | 0.002 | 1.928 | 0.180 | See |
| 3 | KNeighborsClassifier | fit | 0.124 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 5 | 6.446 | NaN | 0.978 | 0.984 | 0.488 | 0.007 | 0.254 | 0.006 | See |
| 4 | KNeighborsClassifier | predict | 35.565 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 0.000 | 0.036 | 0.978 | 0.984 | 3.733 | 0.022 | 9.526 | 0.055 | See |
| 5 | KNeighborsClassifier | predict | 0.196 | 0.014 | 1000000 | 1 | 100 | brute | -1 | 5 | 0.004 | 0.000 | 0.978 | 0.984 | 0.101 | 0.003 | 1.939 | 0.150 | See |
| 6 | KNeighborsClassifier | fit | 0.124 | 0.006 | 1000000 | 1000000 | 100 | brute | -1 | 100 | 6.431 | NaN | 0.978 | 0.984 | 0.484 | 0.023 | 0.257 | 0.017 | See |
| 7 | KNeighborsClassifier | predict | 36.041 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 0.000 | 0.036 | 0.978 | 0.984 | 3.798 | 0.028 | 9.489 | 0.069 | See |
| 8 | KNeighborsClassifier | predict | 0.201 | 0.013 | 1000000 | 1 | 100 | brute | -1 | 100 | 0.004 | 0.000 | 0.978 | 0.984 | 0.101 | 0.003 | 1.985 | 0.134 | See |
| 9 | KNeighborsClassifier | fit | 0.126 | 0.004 | 1000000 | 1000000 | 100 | brute | 1 | 1 | 6.349 | NaN | 0.978 | 0.984 | 0.485 | 0.010 | 0.260 | 0.010 | See |
| 10 | KNeighborsClassifier | predict | 15.004 | 0.158 | 1000000 | 1000 | 100 | brute | 1 | 1 | 0.000 | 0.015 | 0.978 | 0.984 | 3.720 | 0.024 | 4.034 | 0.050 | See |
| 11 | KNeighborsClassifier | predict | 0.199 | 0.008 | 1000000 | 1 | 100 | brute | 1 | 1 | 0.004 | 0.000 | 0.978 | 0.984 | 0.099 | 0.003 | 2.005 | 0.099 | See |
| 12 | KNeighborsClassifier | fit | 0.125 | 0.004 | 1000000 | 1000000 | 100 | brute | 1 | 5 | 6.404 | NaN | 0.978 | 0.984 | 0.481 | 0.011 | 0.260 | 0.010 | See |
| 13 | KNeighborsClassifier | predict | 22.234 | 0.048 | 1000000 | 1000 | 100 | brute | 1 | 5 | 0.000 | 0.022 | 0.978 | 0.984 | 3.704 | 0.022 | 6.003 | 0.038 | See |
| 14 | KNeighborsClassifier | predict | 0.216 | 0.006 | 1000000 | 1 | 100 | brute | 1 | 5 | 0.004 | 0.000 | 0.978 | 0.984 | 0.099 | 0.004 | 2.176 | 0.102 | See |
| 15 | KNeighborsClassifier | fit | 0.123 | 0.005 | 1000000 | 1000000 | 100 | brute | 1 | 100 | 6.498 | NaN | 0.978 | 0.984 | 0.475 | 0.012 | 0.259 | 0.012 | See |
| 16 | KNeighborsClassifier | predict | 24.376 | 0.436 | 1000000 | 1000 | 100 | brute | 1 | 100 | 0.000 | 0.024 | 0.978 | 0.984 | 3.793 | 0.025 | 6.426 | 0.123 | See |
| 17 | KNeighborsClassifier | predict | 0.222 | 0.010 | 1000000 | 1 | 100 | brute | 1 | 100 | 0.004 | 0.000 | 0.978 | 0.984 | 0.100 | 0.005 | 2.214 | 0.157 | See |
| 18 | KNeighborsClassifier | fit | 0.066 | 0.003 | 1000000 | 1000000 | 2 | brute | -1 | 1 | 0.242 | NaN | 0.978 | 0.984 | 0.094 | 0.002 | 0.703 | 0.039 | See |
| 19 | KNeighborsClassifier | predict | 24.741 | 0.019 | 1000000 | 1000 | 2 | brute | -1 | 1 | 0.000 | 0.025 | 0.978 | 0.984 | 0.780 | 0.010 | 31.738 | 0.420 | See |
| 20 | KNeighborsClassifier | predict | 0.021 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 1 | 0.001 | 0.000 | 0.978 | 0.984 | 0.004 | 0.000 | 5.018 | 0.801 | See |
| 21 | KNeighborsClassifier | fit | 0.058 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 5 | 0.274 | NaN | 0.978 | 0.984 | 0.095 | 0.006 | 0.612 | 0.037 | See |
| 22 | KNeighborsClassifier | predict | 31.716 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 0.000 | 0.032 | 0.978 | 0.984 | 0.790 | 0.015 | 40.131 | 0.745 | See |
| 23 | KNeighborsClassifier | predict | 0.031 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 5 | 0.001 | 0.000 | 0.978 | 0.984 | 0.004 | 0.001 | 7.499 | 1.357 | See |
| 24 | KNeighborsClassifier | fit | 0.061 | 0.003 | 1000000 | 1000000 | 2 | brute | -1 | 100 | 0.264 | NaN | 0.978 | 0.984 | 0.093 | 0.001 | 0.653 | 0.034 | See |
| 25 | KNeighborsClassifier | predict | 30.508 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 0.000 | 0.031 | 0.978 | 0.984 | 0.846 | 0.005 | 36.049 | 0.217 | See |
| 26 | KNeighborsClassifier | predict | 0.029 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 100 | 0.001 | 0.000 | 0.978 | 0.984 | 0.004 | 0.001 | 6.866 | 1.083 | See |
| 27 | KNeighborsClassifier | fit | 0.053 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 1 | 0.303 | NaN | 0.978 | 0.984 | 0.096 | 0.005 | 0.551 | 0.027 | See |
| 28 | KNeighborsClassifier | predict | 10.460 | 0.039 | 1000000 | 1000 | 2 | brute | 1 | 1 | 0.000 | 0.010 | 0.978 | 0.984 | 0.790 | 0.011 | 13.247 | 0.189 | See |
| 29 | KNeighborsClassifier | predict | 0.014 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 0.001 | 0.000 | 0.978 | 0.984 | 0.004 | 0.000 | 3.277 | 0.404 | See |
| 30 | KNeighborsClassifier | fit | 0.054 | 0.003 | 1000000 | 1000000 | 2 | brute | 1 | 5 | 0.295 | NaN | 0.978 | 0.984 | 0.093 | 0.002 | 0.581 | 0.029 | See |
| 31 | KNeighborsClassifier | predict | 17.235 | 0.042 | 1000000 | 1000 | 2 | brute | 1 | 5 | 0.000 | 0.017 | 0.978 | 0.984 | 0.785 | 0.008 | 21.950 | 0.233 | See |
| 32 | KNeighborsClassifier | predict | 0.023 | 0.003 | 1000000 | 1 | 2 | brute | 1 | 5 | 0.001 | 0.000 | 0.978 | 0.984 | 0.005 | 0.001 | 4.834 | 1.466 | See |
| 33 | KNeighborsClassifier | fit | 0.053 | 0.002 | 1000000 | 1000000 | 2 | brute | 1 | 100 | 0.299 | NaN | 0.978 | 0.984 | 0.098 | 0.006 | 0.548 | 0.040 | See |
| 34 | KNeighborsClassifier | predict | 17.326 | 0.093 | 1000000 | 1000 | 2 | brute | 1 | 100 | 0.000 | 0.017 | 0.978 | 0.984 | 0.859 | 0.012 | 20.181 | 0.302 | See |
| 35 | KNeighborsClassifier | predict | 0.023 | 0.002 | 1000000 | 1 | 2 | brute | 1 | 100 | 0.001 | 0.000 | 0.978 | 0.984 | 0.004 | 0.000 | 5.458 | 0.784 | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | throughput | latency | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 2.579 | 0.023 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | 0.031 | NaN | 0.983 | 0.984 | 0.719 | 0.011 | 3.586 | 0.065 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.427 | 0.013 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 0.000 | 0.000 | 0.983 | 0.984 | 0.120 | 0.014 | 3.552 | 0.435 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 0.026 | 0.000 | 0.983 | 0.984 | 0.000 | 0.000 | 10.885 | 5.500 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 2.581 | 0.023 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | 0.031 | NaN | 0.983 | 0.984 | 0.727 | 0.012 | 3.548 | 0.067 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.790 | 0.012 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 0.000 | 0.001 | 0.983 | 0.984 | 0.222 | 0.008 | 3.566 | 0.143 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 0.024 | 0.000 | 0.983 | 0.984 | 0.001 | 0.000 | 6.371 | 3.409 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 2.688 | 0.087 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | 0.030 | NaN | 0.983 | 0.984 | 0.686 | 0.014 | 3.916 | 0.151 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 2.798 | 0.023 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 0.000 | 0.003 | 0.983 | 0.984 | 0.645 | 0.008 | 4.340 | 0.064 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 0.018 | 0.000 | 0.983 | 0.984 | 0.001 | 0.000 | 5.579 | 2.125 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 2.769 | 0.037 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | 0.029 | NaN | 0.983 | 0.984 | 0.728 | 0.014 | 3.801 | 0.089 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.768 | 0.016 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 0.000 | 0.001 | 0.983 | 0.984 | 0.119 | 0.003 | 6.480 | 0.195 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 0.069 | 0.000 | 0.983 | 0.984 | 0.000 | 0.000 | 4.891 | 3.280 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 2.735 | 0.061 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | 0.029 | NaN | 0.983 | 0.984 | 0.682 | 0.005 | 4.010 | 0.094 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1.468 | 0.019 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 0.000 | 0.001 | 0.983 | 0.984 | 0.223 | 0.005 | 6.584 | 0.159 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 0.069 | 0.000 | 0.983 | 0.984 | 0.000 | 0.000 | 2.506 | 1.523 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 2.703 | 0.028 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | 0.030 | NaN | 0.983 | 0.984 | 0.725 | 0.015 | 3.727 | 0.085 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 4.758 | 0.079 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 0.000 | 0.005 | 0.983 | 0.984 | 0.665 | 0.012 | 7.153 | 0.179 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 0.031 | 0.000 | 0.983 | 0.984 | 0.001 | 0.000 | 3.265 | 1.855 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 0.707 | 0.024 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | 0.023 | NaN | 0.983 | 0.984 | 0.470 | 0.007 | 1.507 | 0.056 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.034 | 0.003 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 0.000 | 0.000 | 0.983 | 0.984 | 0.001 | 0.001 | 34.916 | 20.514 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 0.006 | 0.000 | 0.983 | 0.984 | 0.000 | 0.000 | 12.974 | 7.040 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 0.702 | 0.015 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | 0.023 | NaN | 0.983 | 0.984 | 0.473 | 0.013 | 1.483 | 0.052 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.035 | 0.004 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 0.000 | 0.000 | 0.983 | 0.984 | 0.001 | 0.001 | 24.617 | 10.387 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 0.006 | 0.000 | 0.983 | 0.984 | 0.000 | 0.000 | 14.910 | 8.850 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 0.699 | 0.016 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | 0.023 | NaN | 0.983 | 0.984 | 0.494 | 0.060 | 1.414 | 0.173 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.054 | 0.003 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 0.000 | 0.000 | 0.983 | 0.984 | 0.007 | 0.001 | 8.104 | 1.018 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.006 | 0.007 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 0.003 | 0.000 | 0.983 | 0.984 | 0.000 | 0.000 | 27.982 | 38.634 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 0.712 | 0.020 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | 0.022 | NaN | 0.983 | 0.984 | 0.473 | 0.005 | 1.507 | 0.045 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.030 | 0.002 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 0.001 | 0.000 | 0.983 | 0.984 | 0.001 | 0.000 | 29.972 | 14.552 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.001 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 0.016 | 0.000 | 0.983 | 0.984 | 0.000 | 0.000 | 6.562 | 4.866 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 0.703 | 0.009 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | 0.023 | NaN | 0.983 | 0.984 | 0.477 | 0.015 | 1.474 | 0.051 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.032 | 0.002 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 0.000 | 0.000 | 0.983 | 0.984 | 0.001 | 0.000 | 27.976 | 8.995 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 0.019 | 0.000 | 0.983 | 0.984 | 0.000 | 0.000 | 5.607 | 3.098 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 0.697 | 0.011 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | 0.023 | NaN | 0.983 | 0.984 | 0.471 | 0.012 | 1.480 | 0.046 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.056 | 0.004 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 0.000 | 0.000 | 0.983 | 0.984 | 0.007 | 0.001 | 8.132 | 1.449 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 0.018 | 0.000 | 0.983 | 0.984 | 0.000 | 0.000 | 5.085 | 2.837 | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | throughput | latency | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.601 | 0.010 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 0.799 | NaN | 0.002 | 30 | 0.002 | 0.293 | 0.007 | 2.054 | 0.059 | See |
| 1 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 0.010 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 7.164 | 2.715 | See |
| 2 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 0.011 | 0.0 | 0.002 | 30 | 0.002 | 0.001 | 0.002 | 1.995 | 4.538 | See |
| 3 | KMeans_tall | fit | 0.497 | 0.009 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30 | 0.966 | NaN | 0.002 | 30 | 0.002 | 0.261 | 0.005 | 1.905 | 0.048 | See |
| 4 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30 | 0.010 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 3.850 | 1.290 | See |
| 5 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30 | 0.011 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 8.112 | 3.452 | See |
| 6 | KMeans_tall | fit | 6.833 | 0.073 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 3.512 | NaN | 0.002 | 30 | 0.002 | 3.867 | 0.035 | 1.767 | 0.025 | See |
| 7 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 0.461 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 5.497 | 1.753 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30 | 0.536 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 8.676 | 3.930 | See |
| 9 | KMeans_tall | fit | 6.396 | 0.066 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30 | 3.753 | NaN | 0.002 | 30 | 0.002 | 3.638 | 0.057 | 1.758 | 0.033 | See |
| 10 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30 | 0.449 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 4.155 | 1.724 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30 | 0.539 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 4.679 | 2.090 | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | throughput | latency | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.314 | 0.013 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 28 | 0.014 | NaN | 0.002 | 25 | 0.006 | 0.140 | 0.008 | 2.250 | 0.152 | See |
| 1 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 28 | 0.008 | 0.0 | 0.002 | 25 | 0.006 | 0.001 | 0.000 | 2.668 | 1.006 | See |
| 2 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 28 | 0.010 | 0.0 | 0.002 | 25 | 0.006 | 0.000 | 0.000 | 9.075 | 4.094 | See |
| 3 | KMeans_short | fit | 0.128 | 0.003 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30 | 0.037 | NaN | 0.002 | 30 | 0.006 | 0.072 | 0.004 | 1.790 | 0.118 | See |
| 4 | KMeans_short | predict | 0.002 | 0.001 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30 | 0.007 | 0.0 | 0.002 | 30 | 0.006 | 0.001 | 0.000 | 2.824 | 1.183 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30 | 0.011 | 0.0 | 0.002 | 30 | 0.006 | 0.000 | 0.000 | 8.514 | 3.961 | See |
| 6 | KMeans_short | fit | 1.003 | 0.033 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 16 | 0.128 | NaN | 0.002 | 24 | 0.006 | 0.590 | 0.041 | 1.700 | 0.130 | See |
| 7 | KMeans_short | predict | 0.003 | 0.001 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 16 | 0.263 | 0.0 | 0.002 | 24 | 0.006 | 0.002 | 0.000 | 1.982 | 0.609 | See |
| 8 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 16 | 0.508 | 0.0 | 0.002 | 24 | 0.006 | 0.000 | 0.000 | 7.433 | 3.715 | See |
| 9 | KMeans_short | fit | 0.324 | 0.039 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 21 | 0.518 | NaN | 0.002 | 23 | 0.006 | 0.296 | 0.040 | 1.096 | 0.198 | See |
| 10 | KMeans_short | predict | 0.003 | 0.001 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 21 | 0.238 | 0.0 | 0.002 | 23 | 0.006 | 0.002 | 0.001 | 2.076 | 0.837 | See |
| 11 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | 21 | 0.518 | 0.0 | 0.002 | 23 | 0.006 | 0.000 | 0.000 | 7.023 | 2.821 | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | throughput | latency | accuracy_score | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 14.759 | 0.269 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | [-0.07994432] | NaN | 0.32 | 14.526 | 0.030 | 1.016 | 0.019 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 2.1398418758814652 | 0.0 | 0.32 | 0.000 | 0.000 | 0.885 | 0.512 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 7.82015214239195 | 0.0 | 0.32 | 0.000 | 0.000 | 0.420 | 0.273 | See |
| 3 | LogisticRegression | fit | 1.267 | 0.021 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [29] | [-1.55846835] | NaN | 0.32 | 1.162 | 0.032 | 1.091 | 0.035 | See |
| 4 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [29] | 3.4293835067229668 | 0.0 | 0.32 | 0.004 | 0.001 | 0.570 | 0.090 | See |
| 5 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [29] | 61.806559355642875 | 0.0 | 0.32 | 0.001 | 0.000 | 0.152 | 0.081 | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | deprecated |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | throughput | latency | r2_score | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 0.269 | 0.005 | 1000 | 1000 | 10000 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 0.297 | NaN | 1.0 | 0.278 | 0.005 | 0.968 | 0.026 | See |
| 1 | Ridge | predict | 0.011 | 0.001 | 1000 | 1000 | 10000 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 7.563 | 0.0 | 1.0 | 0.017 | 0.001 | 0.615 | 0.058 | See |
| 2 | Ridge | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 795.468 | 0.0 | 1.0 | 0.000 | 0.000 | 0.644 | 0.438 | See |
| 3 | Ridge | fit | 1.140 | 0.035 | 1000000 | 1000000 | 100 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 0.702 | NaN | 1.0 | 0.320 | 0.006 | 3.559 | 0.128 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 2.584 | 0.0 | 1.0 | 0.000 | 0.000 | 1.063 | 0.743 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 4.524 | 0.0 | 1.0 | 0.000 | 0.000 | 1.067 | 0.574 | See |
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